Version 1
: Received: 26 July 2024 / Approved: 27 July 2024 / Online: 30 July 2024 (11:47:30 CEST)
How to cite:
Abojayab, G.; Guvenis, A. Comparative Analysis of OSEM Parameters for Cardiac SPECT Imaging Across Multiple Camera Brands: A Monte Carlo Study. Preprints2024, 2024072232. https://doi.org/10.20944/preprints202407.2232.v1
Abojayab, G.; Guvenis, A. Comparative Analysis of OSEM Parameters for Cardiac SPECT Imaging Across Multiple Camera Brands: A Monte Carlo Study. Preprints 2024, 2024072232. https://doi.org/10.20944/preprints202407.2232.v1
Abojayab, G.; Guvenis, A. Comparative Analysis of OSEM Parameters for Cardiac SPECT Imaging Across Multiple Camera Brands: A Monte Carlo Study. Preprints2024, 2024072232. https://doi.org/10.20944/preprints202407.2232.v1
APA Style
Abojayab, G., & Guvenis, A. (2024). Comparative Analysis of OSEM Parameters for Cardiac SPECT Imaging Across Multiple Camera Brands: A Monte Carlo Study. Preprints. https://doi.org/10.20944/preprints202407.2232.v1
Chicago/Turabian Style
Abojayab, G. and Albert Guvenis. 2024 "Comparative Analysis of OSEM Parameters for Cardiac SPECT Imaging Across Multiple Camera Brands: A Monte Carlo Study" Preprints. https://doi.org/10.20944/preprints202407.2232.v1
Abstract
Background and Objective: To examine the effect of ordered subset expectation maximization (OSEM) parameters on the quantitative image quality of cardiac SPECT images in two different frequently used SPECT cameras and determine the optimal settings for producing images of best diagnostic quality. Another objective was to assess if different cameras produced a significant change in optimal parameters and levels of detectability. Methods: The optimization of OSEM iterative reconstruction algorithm was carried out by comparing image quality metrics, namely, contrast-to-noise ratio (CNR) and defect contrast across 12 OSEM subset-iteration combinations to find the best choice for cardiac perfusion SPECT images. Eight frames were reconstructed using the SIMIND Monte Carlo Simulation package. An activity of 370 MBq (10mCi) and projection acquisition interval of 20 seconds per projection were used. Attenuation (AC) and scatter corrections (SC) were performed in this study for all images. Results: The 16-2 subset-iteration combination yielded the highest CNR and defect contrast values for both cameras. The difference between CNR values for two cameras was found to be around 5% only. Conclusions: Monte Carlosimulations can be useful to investigate how quantitative image quality behaves with respect to reconstruction parameters and correction algorithms in a controlled environment. The found optimum is similar to values reported in previous findings. In this study, the use of different camera brands did not affect the optimum. The quantitative detectability measures were also very similar.
Keywords
myocardial perfusion imaging; single photon emission computed tomography; contrast-to-noise ratio; SNR; Monte Carlo; SIMIND
Subject
Physical Sciences, Radiation and Radiography
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
